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Research on stochastic resonance enhancement of X-ray images based on a genetic algorithm

机译:基于遗传算法的X射线图像随机共振增强研究

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摘要

Due to the poor enhancement of a faint image in X-ray images, a novel method based on the scale-variable stochastic resonance model is proposed in this paper. Firstly, the effect of the stochastic resonance model parameters on the enhanced image quality is analysed. Then, for obtaining the optimum model parameters, a stochastic resonance image enhancement method based on a genetic optimisation algorithm is proposed. The genetic algorithm employs an image quality evaluation index as the fitness function, which can indicate the variety of image quality. Making full use of parallel optimisation of the genetic optimisation algorithm and weak signal enhancement of the stochastic resonance, the proposed method overcomes the poor enhancement of traditional methods. The proposed method was applied to simulated images and typical defect images. Experimental results confirmed its effectiveness in increasing the visibility of images.
机译:由于X射线图像中模糊图像的增强效果较差,本文提出了一种基于比例可变的随机共振模型的新方法。首先,分析了随机共振模型参数对增强图像质量的影响。然后,为了获得最优的模型参数,提出了一种基于遗传优化算法的随机共振图像增强方法。遗传算法采用图像质量评价指标作为适应度函数,可以指示图像质量的变化。该方法充分利用了遗传优化算法的并行优化和随机共振的弱信号增强功能,克服了传统方法的增强效果。将该方法应用于模拟图像和典型缺陷图像。实验结果证实了其在增加图像可见度方面的有效性。

著录项

  • 来源
    《Insight 》 |2016年第5期| 246-250| 共5页
  • 作者单位

    College of Engineering, Ocean University of China, Qingdao 266100, China;

    College of Engineering, Ocean University of China, Qingdao 266100, China;

    College of Engineering, Ocean University of China, Qingdao 266100, China;

    College of Engineering, Ocean University of China, Qingdao 266100, China;

    College of Engineering, Ocean University of China, Qingdao 266100, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    X-ray image enhancement; stochastic resonance; genetic algorithm;

    机译:X射线图像增强;随机共振遗传算法;

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